We want participants to be able to write programmes in the Python programming language, use Numpy, Pandas, and Matplotlib data science libraries, preprocess data using Sci-kit Learning, and use machine learning to carry out a variety of tasks, including regression, classification, clustering, and other operations.

Participants are expected to assess machine learning models using a variety of evaluation techniques. Some of the models we will learn here include Decision Tree and Random Forest, SVM, and K-Means Clustering. We will also learn about linear regression and polynomial regression models.

This course is intermediate in difficulty. You ought to be familiar with the fundamentals of Python programming. We will use mathematical jargon like vector matrix, vector matrix operation, and matrix multiplication because this is a machine learning course.

You ought to be knowledgeable about software. To write Python code, we'll be utilising Google Collab. This should also work if you are familiar with Jupiter Notebook.

Course Duration:- 5h 31m